人工智能和放射学:在免疫治疗中治疗晚期黑色素瘤患者的临床应用
Jeremy McGale1, Jakob Hama2, Randy Yeh3
1Department of Radiology, New York-Presbyterian Hospital, New York, NY 10032, USA.
Diagnostics (Basel, Switzerland)
|October 14, 2023
概括
人工智能 (AI) 在预测接受免疫治疗的黑色素瘤患者的结果方面表现有希望. 需要进一步进行强有力的验证研究,以将AI工具集成到临床实践中,以便更好地选择患者和预测治疗反应.
科学领域:
- 在瘤学瘤学.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 免疫疗法已经推进了转移性黑色素瘤的治疗,但预测患者的结果和不良事件仍然具有挑战性.
- 需要改善生物标志物以指导治疗决策并确定长期受益的患者.
研究的目的:
- 审查人工智能 (AI) 的应用,包括放射学,机器学习和深度学习,在接受免疫治疗的黑色素瘤患者中.
- 识别黑色素瘤免疫治疗人工智能研究的当前趋势,方法和局限性.
主要方法:
- 一项针对2022年初发表的12项关于免疫疗法治疗黑色素瘤的人工智能研究的专注文献调查.
- 分析成像模式,研究设计,人工智能应用 (预测,响应预测) 和验证方法.
主要成果:
- 计算机断层扫描 (CT) 成像是最常见的模式 (75%).
- 大多数研究都专注于人工智能用于预后 (41.7%) 或治疗反应预测 (50.0%),经常使用回顾性,单一机构数据 (58.3%).
- 验证方法高度可变,严格的前性验证的使用有限.
结论:
- 人工智能显示出增强黑色素瘤免疫治疗结果的有希望的潜力.
- 使用多样化,潜在的患者队伍进行严格的验证对于AI工具的临床集成至关重要.
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